It is often required to securely determine a result of applying a function to signals. For example, two processors, e.g., Alice and Bob, have signals x and y, respectively. A third processor, Charlie, is requested to determine a result of a function ƒ(x, y). However, Charlie is not to receive any knowledge about the signals x and y, and Alice and Bob are not to receive any knowledge about each other's signals.
For example, a third party agency needs to analyze statistics about diseases of patients in a number of hospitals. With concerns over the privacy of the patients, each hospital must ensure that this analysis can be performed without divulging private information of the patients.
Such problems are often solved by secure multiparty computation (SMC). Computationally secure methods, such as oblivious transfer (OT), secure inner product (SIP) can be used as primitives to perform more complicated operations. U.S. patent application Ser. No. 11/005,293 describes such a method. That method performs secure classification of an image supplied to a third party by a user. The third party cannot determine the image, and the user cannot determine the classification method. However, methods based on oblivious transfer incur a large communication overhead, in terms of key exchanges and data transfers between the constituent parties.